Abstract
Background: Immune and skeletal systems physiologically and pathologically interact with each other. Immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown.
Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia, and fracture).
Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. The versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA.
Results: About 157 (p<8.19E-6), 319 (p<3.90E-6), and 77 (p<9.72E-6) potential pleiotropic genes
were identified shared by two immune diseases, four skeletal diseases, and all of the six diseases,
respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal
diseases, including HLA-B, TSBP1, and TSBP1-AS1 (p
Keywords: GWAS, metaCCA, VEGAS2, pleiotropic gene, immune diseases, skeletal diseases.
Graphical Abstract
Current Genomics
Title:Identification of Potential Pleiotropic Genes for Immune and Skeletal Diseases Using Multivariate MetaCCA Analysis
Volume: 22 Issue: 8
Author(s): Pei He, Rong- Rong Cao , Fei- Yan Deng and Shu- Feng Lei *
Affiliation:
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123, P. R. ,China
Keywords: GWAS, metaCCA, VEGAS2, pleiotropic gene, immune diseases, skeletal diseases.
Abstract: Background: Immune and skeletal systems physiologically and pathologically interact with each other. Immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown.
Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia, and fracture).
Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. The versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA.
Results: About 157 (p<8.19E-6), 319 (p<3.90E-6), and 77 (p<9.72E-6) potential pleiotropic genes
were identified shared by two immune diseases, four skeletal diseases, and all of the six diseases,
respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal
diseases, including HLA-B, TSBP1, and TSBP1-AS1 (p
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Cite this article as:
He Pei , Cao Rong Rong-, Deng Yan Fei- and Lei Feng Shu-*, Identification of Potential Pleiotropic Genes for Immune and Skeletal Diseases Using Multivariate MetaCCA Analysis, Current Genomics 2021; 22 (8) . https://dx.doi.org/10.2174/1389202923666211223115214
DOI https://dx.doi.org/10.2174/1389202923666211223115214 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
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